Cross-Domain Generalization of a CNN Trained on Oral and Oropharyngeal Squamous Cell Carcinoma Histopathology Using External Validation on Metastatic Lymph Node Tissue. [PDF]
Paun LA +8 more
europepmc +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Disentangling drivers of cross-domain microbial β-variations in intertidal mudflats. [PDF]
Gong X +6 more
europepmc +1 more source
Surgical and hormonal gender-affirming care: cross-domain determinants and artificial intelligence-enabled expansion. [PDF]
Sharma M, Sharma V, De Leo G.
europepmc +1 more source
Development of adaptive activation functions with curvature and range modulation for abstract image feature learning in complex CNNs for cross-domain applications. [PDF]
Raza A, Ali A, Ullah S, Rehman B, Ali Z.
europepmc +1 more source
Longitudinal Patterns of Within- and Cross-Domain Multimorbidity Across Physical, Psychological, and Cognitive Conditions in China and the United States: The Role of Socioeconomic and Healthcare Inequalities. [PDF]
Jia M, Yu Y, Su S.
europepmc +1 more source
Multi-Granularity Domain Adversarial Learning for Cross-Domain Tea Classification Using Electronic Nose Signals. [PDF]
Wang X, Gu Y.
europepmc +1 more source
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This one-day workshop brings together researchers and practitioners to share knowledge and practices of how players are understood, treated and evaluated in specific disciplines and sub-disciplines throughout the diverse field of HCI. Participants from academia and industry will engage in dialogue across these numerous interdisciplinary areas to ...
Gareth R. White +4 more
openaire +2 more sources
Cross-domain activity recognition
Proceedings of the 11th international conference on Ubiquitous computing, 2009In activity recognition, one major challenge is huge manual effort in labeling when a new domain of activities is to be tested. In this paper, we ask an interesting question: can we transfer the available labeled data from a set of existing activities in one domain to help recognize the activities in another different but related domain? Our answer is "
Vincent Wenchen Zheng +2 more
openaire +2 more sources

